Multiword expressions (MWEs) range over linguistic constructions like
idioms (a frog in the throat, kill some time), fixed phrases (per se,
by and large, rock'n roll), noun compounds (traffic light, cable car),
compound verbs (draw a conclusion, go by [a name]), etc. While easily
mastered by native speakers, their interpretation poses a major challenge
for computational systems, due to their flexible and heterogeneous nature.
Surprisingly enough, MWEs are not nearly as frequent in NLP resources
(dictionaries, grammars) as they are in real-word text, where they have
been reported to account for half of the entries in the lexicon of a speaker
and over 70% of the terms in a domain. Thus, MWEs are a key issue and
a current weakness for tasks like natural language parsing and generation,
as well as real-life applications such as machine translation.

In spite of several proposals for MWE representation ranging along the
continuum from words-with-spaces to compositional approaches connecting
lexicon and grammar, to date, it remains unclear how MWEs should be
represented in electronic dictionaries, thesauri and grammars. New
methodologies that take into account the type of MWE and its properties
are needed for efficiently handling manually and/or automatically acquired
expressions in NLP systems. Moreover, we also need strategies to represent
deep attributes and semantic properties for these multiword entries. While
there is no unique definition or classification of MWEs, most researchers
agree on some major classes such as named entities, collocations, multiword
terminology and verbal expressions. These, though, are very heterogeneous
in terms of syntactic and semantic properties, and should thus be treated
differently by applications. Type-dependent analyses could shed some light
on the best methodologies to integrate MWE knowledge in our analysis and
generation systems.

Evaluation is also a crucial aspect for MWE research. Various evaluation
techniques have been proposed, from manual inspection of top-n candidates
to classic precision/recall measures. The use of tools and datasets freely
available on the MWE community website (multiword.sf.net/PHITE.php?sitesig=FILES)
is encouraged when evaluating MWE treatment. However, application-oriented
techniques are needed to give a clear indication of whether the acquired MWEs
are really useful. Research on the impact of MWE handling in applications such
as parsing, generation, information extraction, machine translation, summarization
can help to answer these questions.

We call for papers that present research on theoretical and practical aspects
of the computational treatment of MWEs, specifically focusing on MWEs in
applications such as machine translation, information retrieval and question
answering. We also strongly encourage submissions on processing MWEs in
the language of social media and micro-blogs. The focus of the special issue,
thus, includes, but is not limited to the following topics:

* MWE treatment in applications such as the ones mentioned above;
* Lexical representation of MWEs in dictionaries and grammars;
* Corpus-based identification and extraction of MWEs;
* Application-oriented evaluation of MWE treatment;
* Type-dependent analysis of MWEs;
* Multilingual applications (e.g. machine translation, bilingual dictionaries);
* Parsing and generation of MWEs, especially, processing of MWEs in the
language of social media and micro-blogs;
* MWEs and user interaction;
* MWEs in linguistic theories like HPSG, LFG and minimalism and their
contribution to applications;
* Relevance of research on first and second language acquisition of MWEs for
applications;
* Crosslinguistic studies on MWEs.

Submission Procedure

Authors should follow the ACM TSLP manuscript preparation guidelines
described on the journal web site http://tslp.acm.org and submit an
electronic copy of their complete manuscript through the journal manuscript
submission site http://mc.manuscriptcentral.com/acm/tslp. Authors are required
to specify that their submission is intended for this special issue by including
on the first page of the manuscript and in the field "Author's Cover Letter" the
note "Submitted for the special issue on Multiword Expressions".